光谱学与光谱分析 |
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Airborne Validation of Ground-Object Detection from Polarized Neutral-Point Atmosphere |
YANG Shang-qiang1,2, GUAN Gui-xia1, ZHAO Hai-meng2, ZHAO Hong-ying2, YANG Bin2, ZHANG Wen-kai1,2, TAN Xiang2,4, WU Tai-xia3, YAN Lei2* |
1. College of Information Engineering, Capital Normal University, Beijing 100048, China 2. Beijing Key Lab of Spatial Information Integration and Its Applications, Peking University, Beijing 100871, China 3. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China 4. Specialized Forces College of Chinese Armed Police Force, Beijing 102202, China |
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Abstract Based on the objects polarization effects, polarization is a newly emerging method in the field of remote sensing. Both objects and atmosphere have polarization effects, however, the atmospheres polarization effects are much stronger than that of objects. Consequently, atmosphere polarization effects will interfere or even cover objects when observing with sensors. How to maximally eliminate the polarized effects generated by the atmosphere is a crucial problem in polarization remote sensing. Atmospheric neutral point is an area where the degree of atmosphere polarization is near to zero; therefore, if sensors are set up in this area, atmosphere polarization would be greatly eliminated, which is the main content of separating the effects between objects and atmosphere by its neutral point method. In this paper, after processing and analyzing the experimental data got from the first polarization remote sensing flight experiment with atmosphere neutral point, the degree of polarization images captured in neutral and non-neutral point area were obtained, and it can be seen that the main value of polarized degree of images got in neutral point area was obviously smaller than that in non-neutral point area. The results showed that the theory mentioned above was logical and practical. An innovation in our study is that the requirements needed in polarization remote sensing flight with neutral point were clarified. In the meantime, a qualitative conclusion was drawn that observing with longer wavelength is more applicable to polarization remote sensing.
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Received: 2013-03-17
Accepted: 2013-07-19
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Corresponding Authors:
YAN Lei
E-mail: lyan@pku.edu.cn
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[1] Schott J R. Fundamentals of Polarimetric Remote Sensing. Bellingham. Washington: Society of Photo Optical, 2009. [2] Wu Taixia, Zhao Yunsheng. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(12): 2854. [3] Talmage D A, Curran P J. International Journal of Remote Sensing,1986, 7(1): 47. [4] Cheng Tianhai, Gu Xingfa, et al. Acta Physica Sinica, 2009, 58(10): 7368. [5] Lee R L. Appl. Opt., 1998, 37:1465. [6] Nadal F, Breon F M. IEEE Transactions on Geoscience and Remote Sensing. 1999, 37(3): 1709. [7] Sheng Peixuan, Mao Jietai, Li Jianguo. Atmospheric Physics. Beijing:Peking University Press, 2003. [8] Wu Taixia. Study on the Land Objects Characteristics and the Separation Method for the Effect Between Objects and Atmosphere in Polarization Remote Sensing. Ph.D. Thesis, Peking University. 2010. [9] Berry M V, Dennis M R, Lee R L. Polarization Singularities in the Clear Sky. New Journal of Physics,2004. 6. [10] Muhem R, Phillips J B, Akesson S. Science, 2006, 313(5788): 837. [11] Coulson K L. Polarization and Intensity of Light in the Atmosphere. Hampton, Va, USA: A. Deepak Pub, 1988. 596. [12] Guan Guixia, Yan Lei, Chen Jiabin. Computer Applications and Software,2009, 26(12): 179. [13] Yan Lei, Guan Guixia, Chen Jiabin, et al. Acta Scientiarum Naturalium Universitais Pekinensis (ASNUP), 2009,45(4):616.
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